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UID:30@csb.utoronto.ca
DTSTART;TZID=America/Toronto:20260109T110000
DTEND;TZID=America/Toronto:20260109T120000
DTSTAMP:20251210T145334Z
URL:https://csb.utoronto.ca/events/cheng-huang-phd-department-of-neuroscie
 nce-university-washington-csb-seminar/
SUMMARY:Cheng Huang\, PhD - Department of Neuroscience\, Washington Univers
 ity School of Medicine in St. Louis  -- CSB Seminar
DESCRIPTION:CSB Departmental Seminar\nFriday\, January 9th @ 11:00 am\nSPEA
 KER: Cheng Huang\, PhD - Department of Neuroscience\, Washington Universit
 y School of Medicine in St. Louis\nTITLE: Decoding dopamine-mediated lear
 ning algorithms in the Drosophila brain\nABSTRACT: My research program foc
 uses on understanding the neural circuits underlying memory formation\, st
 orage\, and retrieval. Using Drosophila as a model system\, I am particula
 rly interested in how dopamine signaling modulates neural plasticity and c
 ontributes to adaptive behaviors. We employ a multidisciplinary approach\,
  combining advanced imaging techniques\, quantitative behavioral assays\, 
 and computational modeling to dissect the complex dynamics of dopamine neu
 rons during learning and memory processes. Our latest study reveals how in
 nate valence information regulates memory dynamics and uncovers a mechanis
 m by which short-term memory gates long-term memory formation through dopa
 mine signaling. Specifically\, we examined the MB circuit for learning ave
 rsive associations. First\, we discovered a subset of dopamine neurons tha
 t encode negative innate sensory valence information. During learning\, th
 ese dopamine neurons dynamically integrate this innate valence with learne
 d associations (e.g.\, the association of the odor with an electric shock)
 . This integrated valence signal then controls long-lasting neural plastic
 ity in downstream neurons. To understand how this learned valence arises\,
  we identified an inhibitory feedback pathway from short-term memory encod
 ing neurons to the dopamine neurons. This pathway underlies the learned va
 lence represented in the dopamine signal\, ensuring that only consistent a
 ssociations generate long-lasting memories. Further\, we constructed a com
 putational model using constraints derived from both our large-scale volta
 ge imaging dataset and Drosophila connectome data. We uncovered the comput
 ational principle and benefits of dopamine-based valence integration in th
 is learning network. Collectively\, our results provide insights into how 
 ecologically relevant information directly governs memory formation and de
 monstrate the power of integrative research approaches in studying complex
  brain processes.\n\nHOST: Qian Lin\nLOCATION: Cell and Systems Biology\,
  25 Harbord Street\, Suite 432\nLIVESTREAM LINK: https://csb.utoronto.ca/
 live-stream/
CATEGORIES:seminar
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